Intelligence without representation
Artificial Intelligence
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Explorations in evolutionary robotics
Adaptive Behavior
Robotic experiments in cricket phonotaxis
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
An introduction to genetic algorithms
An introduction to genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Action as a Fast and Frugal Heuristic
Minds and Machines
Simplicity and Robustness of Fast and Frugal Heuristics
Minds and Machines
Simple Inference Heuristics versus Complex Decision Machines
Minds and Machines
Competitive foraging, decision making, and the ecological rationality of the matching law
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Compositional Syntax From Cultural Transmission
Artificial Life
Decision Theory, Intelligent Planning and Counterfactuals
Minds and Machines
How the Web Is Changing the Way We Trust
Proceedings of the 2008 conference on Current Issues in Computing and Philosophy
Situated cognition and the role of multi-agent models in explaining language structure
Adaptive agents and multi-agent systems
Self-organizing agent communities for autonomic resource management
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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A working assumption that processes of natural and cultural evolution have tailored the mind to fit the demands and structure of its environment begs the question: how are we to characterize the structure of cognitive environments? Decision problems faced by real organisms are not like simple multiple-choice examination papers. For example, some individual problems may occur much more frequently than others, whilst some may carry much more weight than others. Such considerations are not taken into account when (i) the performance of candidate cognitive mechanisms is assessed by employing a simple accuracy metric that is insensitive to the structure of the decision-maker's environment, and (ii) reason is defined as the adherence to internalist prescriptions of classical rationality. Here we explore the impact of frequency and significance structure on the performance of a range of candidate decision-making mechanisms. We show that the character of this impact is complex, since structured environments demand that decision-makers trade off general performance against performance on important subsets of test items. As a result, environment structure obviates internalist criteria of rationality. Failing to appreciate the role of environment structure in shaping cognition can lead to mischaracterising adaptive behavior as irrational.